scholarly journals Research on Biomechanical Simulation and Simulation of Badminton Splitting and Hanging Action Based on Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Bo Zhang
Keyword(s):  
Genetic Algorithm ◽  
New Technology ◽  
Digital Simulation ◽  
Transmission Efficiency ◽  
Edge Computing ◽  
Theoretical Research ◽  
Simulation Research ◽  
Biomechanical Simulation ◽  
Process System ◽  
Sports Biomechanics

Sports biomechanics refers to the science of the laws of mechanical motion produced in the process of biological movement. Its essence is to systematically and digitally reconstruct the fundamental attributes and characteristics of motion. At present, the research of sports biomechanics mainly focuses on the theoretical research of basic aspects and lacks the new technology of sports biomechanics digital simulation innovation and data measurement. This article takes the badminton chopping action as the research object and carries out biomechanical simulation and simulation research with the help of edge computing and genetic algorithm. First of all, this paper constructs a badminton chopping and hanging action system framework based on edge computing, so as to facilitate simulation and improve data transmission efficiency. Secondly, genetic algorithm is used in biomechanics simulation and simulation optimization and data analysis process. System testing and simulation verify the excellent performance of the biomechanical simulation of badminton chopping and hanging action established in this paper. The research will provide a reference for the academic circles to explore the field of sports biomechanics.

Compensating Resonant Frequency via Adjusting Adjustable Coil Automatically

2019 ◽  
Vol 12 (5) ◽  
pp. 432-438
Author(s):  
Jin Xu ◽  
Yuting Zhao
Keyword(s):  
Resonant Frequency ◽  
Power Transmission ◽  
Reference Value ◽  
Transmission Efficiency ◽  
Theoretical Research ◽  
Future Research ◽  
Wireless Power ◽  
Wireless Power Transmission ◽  
Resonant Coupling ◽  
Transmission Distance

Background: Detuning is the main problem that affects the efficiency and transmission distance of the resonant coupling Wireless Power Transmission (WPT). The distance of load and the offset of the load position could cause serious detuning. Methods: This paper presents an adjustable coil in which inductance can be adjusted. Then a model of WPT was established that could compensate resonant frequency automatically using the adjustable coil. Next, the relationship between the primary resonant frequency and the transmission efficiency is analyzed from the circuit. The analysis proved that the design of the adjustable coil could improve the transmission efficiency of the WPT system. Finally, a prototype of WPT system was built. Results: The experimental results showed that WPT system with adjustable coil can improve the transmission efficiency which proves the theoretical research. At the same time, it has essential reference value for the future research of WPT. Conclusion: In this paper, aiming at the system detuning caused by some other factors, such as the position shift of the load during the wireless power transmission, an adjustable coil is proposed.

scholarly journals Adaptive offloading in mobile-edge computing for ultra-dense cellular networks based on genetic algorithm

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Zhuofan Liao ◽  
Jingsheng Peng ◽  
Bing Xiong ◽  
Jiawei Huang
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Cellular Networks ◽  
Physical Distance ◽  
Edge Computing ◽  
Base Stations ◽  
Mobile Edge Computing ◽  
Total Energy Consumption ◽  
Average Delay ◽  
Server Selection

AbstractWith the combination of Mobile Edge Computing (MEC) and the next generation cellular networks, computation requests from end devices can be offloaded promptly and accurately by edge servers equipped on Base Stations (BSs). However, due to the densified heterogeneous deployment of BSs, the end device may be covered by more than one BS, which brings new challenges for offloading decision, that is whether and where to offload computing tasks for low latency and energy cost. This paper formulates a multi-user-to-multi-servers (MUMS) edge computing problem in ultra-dense cellular networks. The MUMS problem is divided and conquered by two phases, which are server selection and offloading decision. For the server selection phases, mobile users are grouped to one BS considering both physical distance and workload. After the grouping, the original problem is divided into parallel multi-user-to-one-server offloading decision subproblems. To get fast and near-optimal solutions for these subproblems, a distributed offloading strategy based on a binary-coded genetic algorithm is designed to get an adaptive offloading decision. Convergence analysis of the genetic algorithm is given and extensive simulations show that the proposed strategy significantly reduces the average latency and energy consumption of mobile devices. Compared with the state-of-the-art offloading researches, our strategy reduces the average delay by 56% and total energy consumption by 14% in the ultra-dense cellular networks.

Multi-objective optimization of hydro-viscous flexible drive for dynamic characteristics using genetic algorithm

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jianzhong Cui ◽  
Hu Li ◽  
Dong Zhang ◽  
Yawen Xu ◽  
Fangwei Xie
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Characteristics ◽  
Transmission Efficiency ◽  
Outer Radius ◽  
Transmission Model ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Dynamic Transmission Model

Purpose The purpose of this study is to investigate the flexible dynamic characteristics about hydro-viscous drive providing meaningful insights into the credible speed-regulating behavior during the soft-start. Design/methodology/approach A comprehensive dynamic transmission model is proposed to investigate the effects of key parameters on the dynamic characteristics. To achieve a trade-off between the transmission efficiency and time proportion of hydrodynamic and mixed lubrication, a multi-objective optimization of friction pair system by genetic algorithm is presented to obtain the optimal combination of design parameters. Findings Decreasing the engagement pressure or the ratio of inner and outer radius, increasing the lubricating oil viscosity or the outer radius will result in the increase of time proportion of hydrodynamic and mixed lubrication, as well as the transmission efficiency and its maximum value. After optimization, main dynamic parameters including the oil film thickness, angular velocity of the driven disk, viscous torque and total torque show remarkable flexible transmission characteristics. Originality/value Both the dynamic transmission model and multi-objective optimization model are established to analyze the effects of main design parameters on the dynamic characteristics of hydro-viscous flexible drive.

Grefenstette Bias based genetic algorithm for multi-site offloading using docker container in edge computing

2019 ◽  
Vol 36 (3) ◽  
pp. 2419-2429 ◽  
Author(s):  
R. Ezhilarasie ◽  
A. Umamakeswari ◽  
Mandi Sushmanth Reddy ◽  
P. Balakrishnan
Keyword(s):  
Genetic Algorithm ◽  
Edge Computing

Fuzzy Reliablity Optimization Design of Two Stage Planetary Gear System by Genetic Algorithm Based on Predatory Search Strategy

2011 ◽  
Vol 403-408 ◽  
pp. 743-747 ◽  
Author(s):  
Chun Guang Wang
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Reliability Analysis ◽  
Optimization Design ◽  
Search Strategy ◽  
Planetary Gear ◽  
Transmission Efficiency ◽  
Fuzzy Reliability ◽  
Two Stage ◽  
Planetary Gear Sets

Fuzzy reliability analysis is regared as the theoretical basis. It takes the minimum volume and the maximum transmission efficiency as objective function．Then the mathematical model of fuzzy reliability optimal design on two stage planetary gear sets is set up. Genetic algorithm based on predatory search strategy is used to solve the fuzzy reliability mathematical model. Examples of calculation shows that the volume is decrease by 15%. The results imply the fuzzy reliability analysis is more scientific and reasonable in designing two stage planetary gear sets by using fuzzy reliability analysis.

Modeling and Simulation Research on Lithium-Ion Battery in Electric Vehicles Based on Genetic Algorithm

2014 ◽  
Vol 494-495 ◽  
pp. 246-249
Author(s):  
Cheng Lin ◽  
Xiao Hua Zhang
Keyword(s):  
Genetic Algorithm ◽  
Lithium Ion Battery ◽  
Stress Test ◽  
Lithium Ion ◽  
Model Parameters ◽  
Test Accuracy ◽  
Battery Management System ◽  
Battery Management ◽  
Simulation Research ◽  
Battery Model

Based on the genetic algorithm (GA), a novel type of parameters identification method on battery model was proposed. The battery model parameters were optimized by genetic optimization algorithm and the other parameters were identified through the hybrid pulse power characterization (HPPC) test. Accuracy and efficiency of the battery model were validated with the dynamic stress test (DST). Simulation and experiment results shows that the proposed model of the lithium-ion battery with identified parameters was accurate enough to meet the requirements of the state of charge (SoC) estimation and battery management system.

Intrusion Detection Model Based on Improved Genetic Algorithm Neural Network in Computer Integrated Process System

2013 ◽  
Vol 380-384 ◽  
pp. 2708-2711
Author(s):  
Li Kun Zou ◽  
Shao Kun Liu ◽  
Guo Fu Ma
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Intrusion Detection ◽  
Detection System ◽  
Linear Mapping ◽  
Integrated Process ◽  
Detection Model ◽  
Model Based ◽  
Fitness Value ◽  
Process System

In order to solve the problems of high false alarm rate and fail rate in intrusion detection system of Computer Integrated Process System (CIPS) network, this paper takes advantage that Genetic Algorithm (GA) possesses overall optimization seeking ability and neural network has formidable approaching ability to the non-linear mapping to propose an intrusion detection model based on Genetic Algorithm Neural Network (GANN) with self-learning and adaptive capacity, which includes data collection module, data preprocessing module, neural network analysis module and intrusion alarm module. To overcome the shortcomings that GA is easy to fall into the extreme value and searches slowly, it improves the adjusting method of GANN fitness value and optimizes the parameter settings of GA. The improved GA is used to optimize BP neural network. Simulation results show that the model makes the detection rate of the system enhance to 97.11%.

Research on Logistics Distribution Route Based on Multi-objective Sorting Genetic Algorithm

2020 ◽  
Vol 29 (07n08) ◽  
pp. 2040020
Author(s):  
Jun Zhao ◽  
Hui Xiang ◽  
Jinbao Li ◽  
Jie Liu ◽  
Luyao Guo
Keyword(s):  
Genetic Algorithm ◽  
Programming Model ◽  
Optimal Path ◽  
Reference Value ◽  
Theoretical Research ◽  
Logistics System ◽  
Logistics Distribution ◽  
Multi Objective ◽  
Elite Strategy ◽  
Low Dimensional

With the continuous development of society, the social division of labor is further improved, and social production tends to be highly specialized and industrialized. Moreover, enterprise production is increasingly internationalized, and sales are gradually expanding. Therefore, the multi-objective sequencing in logistics distribution is incorporated into the path optimization of the logistics system, and a multi-objective bi-level programming model of time and cost is established. What is more, considering the limitations of the traditional algorithm in solving multi-objective problems, the low-dimensional multi-objective problem is selected, and according to the actual situation, the inheritance strategy of genetic factors is adopted to solve the more targeted rapid dominating sorting genetic problem. Besides, the specific conditions and characteristics of the model determine the encoding method, which is brought into the operation of the cross-mutation law and the interruption of individual populations, so that the building foundation of the model is improved. Based on the further theoretical research on the distribution efficiency of logistics system, the corresponding mathematical model is constructed by using the planning method, and the single cost target is transformed into the time and cost double objective, and the improved fast non dominated sorting genetic algorithm with elite strategy is used to solve the problem, which has certain theoretical innovation. Through simulation, the optimal or near optimal path of distribution vehicles in a certain area is given, which has certain practicality and reference value for the optimization of actual logistics distribution path.

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